1. Mohammad Malli Chadi Barakat, Walid Dabbous Alcatel meeting
A Dynamic Architecture for Reducing the Response Time and Avoiding the Congestion
Mohammad Malli Chadi Barakat, Walid Dabbous Alcatel meeting

2. Outline Introduction & goal Proposed solutions
Our scheme: Application-layer anycasting
Transfer time prediction
Prediction evaluation
Conclusions
June, 2004

3. Introduction
Service replication consists in providing the same service from many mirror servers distributed geographically
a service can be : software, mp3, real-time audio or video streaming, etc.
can be replicated in CDN (e.g. Akamai), P2P (e.g. Kazaa)
Anycast : a client request must be served by one server among a set of replicated servers
Which criterias must be considered to choose the server ?
June, 2004

4. Goal
Our aim is to localize the best server in order to minimize the time required to serve a client
We consider a service that consists in client downloading files from a set of replicated servers using the TCP protocol
QoS provided to clients is maximized if the transfer time is minimized
Avoid network and server congestion by considering the available bw, RTT, packet loss rate on the path and the servers load
the feasibility to implement the scheme
June, 2004

5. Existing solutions
IP anycasting : best effort delivery of an anycast datagram
difficult to be deployed since it requires to be implemented in routers
DNS : distribute the IP addresses with a round robin algorithm
Offering the addresses of all the mirror servers in a web page and let the client choose
Other propositions : Consider the network proximity, performance on the path
client - server distance : geographic proximity, nb of hops, RTT, etc.
binning strategy : client must measure the RTT with a set of landmark points,
2 tier strategy : using client proxies to estimate the performance on the path with the servers and register the servers load, etc.
June, 2004

6. Lessons application layer anycasting :
more efficient and easy to deploy
performance on the path server - client must be considered :
available bandwidth, round trip time, packet loss rate
server load and buffering capacity must be considered :
request waiting time, maximum receiving window
the best server must be characterized transparently to the client
the scheme must be scalable and must not require an expansive
implementation
June, 2004

7. The determination of the best server is hidden regarding the client:
Our scheme
The determination of the best server is hidden regarding the client:
June, 2004

8. Application-layer anycasting architecture :
Our scheme
Application-layer anycasting architecture :
each server, among a chosen set, computes our predicted transfer time metric PTT
the central server compares between the different PTT values to obtain an ordered list from the best server to the worst one
June, 2004

9. Transfer time prediction
Transfer time of a content transmitted using TCP :
E[Ts] : Mean request waiting time in the server :
E[Lss] is the transfer time passed during the slow start phase
E[Lca] is the transfer time passed during the congestion avoidance phase
June, 2004

10. Transfer time prediction
Max. sending rate that can be reached at the end of the slow start phase :
TCP average throughput in the congestion avoidance phase or in the steady state :
the transfer can be completed before reaching Rmax :
June, 2004

11. Transfer time prediction
The transfer can be completed after reaching Rmax :
June, 2004

12. Prediction Evaluation
Transfer time prediction when A limits the sending rate
Berlin -> Sophia Antipolis mieux que Paris -> Sophia antipolis
June, 2004

13. Prediction Evaluation
Transfer time prediction when Wmax limits the sending rate :
Transfer time prediction when P limits the sending rate
We obtain an average ratio : PTT over ReTT equal to %
June, 2004

14. Conclusions
Service replication is necessary due to the increasing number of Internet users and the desire to improve the QoS
We propose an efficient scheme for anycasting :
elects the best server based on a metric which can predict the time required to transfer a content between two nodes in the Internet
our metric considers the performance in the network and servers in order to achieve an accurate transfer time prediction and to avoid the congestion
June, 2004

15. Q & A
Thank you
June, 2004